gcloud ai endpoints update

gcloud ai endpoints update - update an existing Vertex AI endpoint

gcloud ai endpoints update (ENDPOINT : --region=REGION) [--description=DESCRIPTION] [--display-name=DISPLAY_NAME] [--update-labels=[KEY=VALUE,…]] [--clear-labels     | --remove-labels=[KEY,…]] [--clear-traffic-split     | --traffic-split=[DEPLOYED_MODEL_ID=VALUE,…]] [--disable-request-response-logging     | --request-response-logging-rate=REQUEST_RESPONSE_LOGGING_RATE --request-response-logging-table=REQUEST_RESPONSE_LOGGING_TABLE] [GCLOUD_WIDE_FLAG …]

Endpoint resource - The endpoint to update. The arguments in this group can be used to specify the attributes of this resource. (NOTE) Some attributes are not given arguments in this group but can be set in other ways.

To set the project attribute:

• provide the argument endpoint on the command line with a fully specified name;
• provide the argument --project on the command line;
• set the property core/project.

This must be specified.

ENDPOINT

ID of the endpoint or fully qualified identifier for the endpoint.

To set the name attribute:

• provide the argument endpoint on the command line.

This positional argument must be specified if any of the other arguments in this group are specified.

--region=REGION

Cloud region for the endpoint.

To set the region attribute:

• provide the argument endpoint on the command line with a fully specified name;
• provide the argument --region on the command line;
• set the property ai/region;
• choose one from the prompted list of available regions.

--description=DESCRIPTION

Description of the endpoint.

--display-name=DISPLAY_NAME

Display name of the endpoint.

--update-labels=[KEY=VALUE,…]

List of label KEY=VALUE pairs to update. If a label exists, its value is modified. Otherwise, a new label is created.

Keys must start with a lowercase character and contain only hyphens (-), underscores (_), lowercase characters, and numbers. Values must contain only hyphens (-), underscores (_), lowercase characters, and numbers.

At most one of these can be specified:

--clear-labels

Remove all labels. If --update-labels is also specified then --clear-labels is applied first.

For example, to remove all labels:

gcloud ai endpoints update --clear-labels

To remove all existing labels and create two new labels, foo and baz:

gcloud ai endpoints update --clear-labels --update-labels foo=bar,baz=qux

--remove-labels=[KEY,…]

List of label keys to remove. If a label does not exist it is silently ignored. If --update-labels is also specified then --update-labels is applied first.

At most one of these can be specified:

--clear-traffic-split

Clears the traffic split map. If the map is empty, the endpoint is to not accept any traffic at the moment.

--traffic-split=[DEPLOYED_MODEL_ID=VALUE,…]

List of pairs of deployed model id and value to set as traffic split.

At most one of these can be specified:

--disable-request-response-logging

Disable prediction request & response logging.

--request-response-logging-rate=REQUEST_RESPONSE_LOGGING_RATE

Prediction request & response sampling rate for logging to BigQuery table.

--request-response-logging-table=REQUEST_RESPONSE_LOGGING_TABLE

BigQuery table uri for prediction request & response logging.

You can provide table uri that does not exist, it will be created for you.

Value should be provided in format: bq://PROJECT_ID/DATASET/TABLE

Run $ gcloud help for details.